Wavelet Subspace Method for Real-Time Face Tracking

In this article we present a new method for visual face tracking that is carried out in wavelet subspace. Firstly, a wavelet representation for the face template is created, which spans a low dimensional subspace of the image space. The wavelet representation of the face is a point in this wavelet subspace. The video sequence frames in which the face is tracked are orthogonally projected into this low-dimensional subspace. This can be done efficiently through a small number of local projections of the wavelet functions. All further computations are then performed in the low-dimensional subspace. The wavelet subspace inherets its invariance to rotation, scale and translation from the wavelets; shear invariance can also be achieved, which makes the subspace invariant to affine deformations.